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Next, we tested whether the prevalence of interactions was influenced by host tree traits.
Several tree traits were non-random distributed in the human-dominated landscape.
The first phase is an off-line learning process, where semantic tree traits perceived by humans are learned.
For all three groups, the difference in prevalence of interaction across modules was determined by a gradient in interaction intimacy (i.e. host tree specialization), driven by host tree traits.
We used one-way analysis of variance (ANOVA) to compare tree traits across the four size-fecundity groups.
We asked: (1) What is the relationship between tree traits, namely stem diameter and fecundity (seed crop size), and patterns of seed dispersal?
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Such a functional trait approach would also help to solve the issue of intraspecific tree trait variations due to e.g. ontogenetic changes.
Allometric model parameters are not restricted to only the above-ground measures of trees' traits (such as stem diameter and height), but also characterize below-ground biomass.
All large-tree traits were unrelated to sapling values and were unrelated to four life-history variables.
We recorded presence/absence of organisms colonizing trees, and traits of host trees, in 102 forest plots.
However, in pear no QTL has been identified that controls tree productivity traits and no genetic analysis has been carried out on rootstocks, although several QTLs have been identified that control traits such as pest and disease resistance [ 16– 18], leaf morphology [ 19], and fruit quality traits [ 20– 20].
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com